Investigating the Interplay between Cardiovascular and Neurodegenerative Disease.

Simple Summary: Traditionally, models of neurodegenerative diseases focus on changes within the central nervous system. However, growing evidence indicates there are prominent interactions between the cardiovascular system and neurodegenerative diseases. In this review, we discuss cardiovascular impairments in models of neurodegeneration, neurological impairments in models of cardiovascular disease, and what occurs when the two are combined as a first step toward improving our understanding of the pathophysiology of neurodegenerative diseases. Neurological diseases, including neurodegenerative diseases (NDDs), are the primary cause of disability worldwide and the second leading cause of death. The chronic nature of these conditions and the lack of disease-modifying therapies highlight the urgent need for developing effective therapies. To accomplish this, effective models of NDDs are required to increase our understanding of underlying pathophysiology and for evaluating treatment efficacy. Traditionally, models of NDDs have focused on the central nervous system (CNS). However, evidence points to a relationship between systemic factors and the development of NDDs. Cardiovascular disease and related risk factors have been shown to modify the cerebral vasculature and the risk of developing Alzheimer's disease. These findings, combined with reports of changes to vascular density and blood–brain barrier integrity in other NDDs, such as Huntington's disease and Parkinson's disease, suggest that cardiovascular health may be predictive of brain function. To evaluate this, we explore evidence for disruptions to the circulatory system in murine models of NDDs, evidence of disruptions to the CNS in cardiovascular disease models and summarize models combining cardiovascular disruption with models of NDDs. In this study, we aim to increase our understanding of cardiovascular disease and neurodegeneration interactions across multiple disease states and evaluate the utility of combining model systems. [ABSTRACT FROM AUTHOR]